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modelling approaches to simulate plasma-assisted combustion systems. This includes developing and validating detailed phenomenological PAC models, implementing coupled plasma–combustion chemical kinetics, and
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, including areas such as tilt series alignment, 2D/3D template matching, or subtomogram averaging. Experience with physics-based modeling or simulation of imaging processes. Familiarity with scientific
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models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 16 days ago
structures and as there are strong occlusions. The 3D reconstruction of flowers has received relatively little study. An early model reconstructs static flowers using botanical priors [1] by building a shape
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. Strong quantitative skills (e.g., econometrics, optimization, I/O table, CGE, simulation modeling) and solid programming experience (e.g., Python/R/Matlab/C). Preferred (optional): familiarity with machine
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
assimilation Integration (JEDI) framework for atmospheric data assimilation Develop machine learning foundation models based on simulated observations from high fidelity atmospheric simulations for developing
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scholarship and applied research, developing prototypes and capabilities that strengthen model-based and data-driven approaches. The position values interdisciplinary thinking, particularly where software
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observations, atmospheric chemistry models, and physics-informed deep learning, validated through field campaigns. Key Responsibilities Conduct atmospheric chemistry simulations Develop deep learning models
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for the in silico models developed as part of the project to determine the model's confidence limits. Development of AI/ML models based on source data from CFD simulations, in vitro, and in vivo studies
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study of wide and ultra-wide bandgap materials and devices and developing device simulation TCAD models to complement experiments when needed. You will also contribute to managing our thermal